Participatory Bayesian network modeling to understand driving factors of land-use change decisions: insights from two case studies in northeast Madagascar

Andriatsitohaina, R. Ntsiva N.; Celio, Enrico; Llopis, Jorge C.; Rabemananjara, Zo H.; Ramamonjisoa, Bruno S.; Grêt-Regamey, Adrienne (2020). Participatory Bayesian network modeling to understand driving factors of land-use change decisions: insights from two case studies in northeast Madagascar. Journal of land use science, 15(1), pp. 69-90. Taylor & Francis 10.1080/1747423x.2020.1742810

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Forest frontiers worldwide reveal trade-offs that are key in mitigating global change. In the forest frontiers of northeast Madagascar, land-use changes result from decisions made by smallholder farmers. In the past, subsistence needs led to increasing shifting cultivation, resulting in forest degradation and deforestation. This study focuses on investigating the role of locally determined factors in land-use change decisions in the forest frontier context. Therefore, we developed a Bayesian network-based land-use decision model that represents the causalities between factors influencing land-use decisions and takes into account local decision-makers’ knowledge. The approach is applied in two comparative case studies in northeast Madagascar. Results show that farmers mostly aim at extending the cultivation of cash crops. These results and the causal mechanisms disentangled for the forest frontier of northeast Madagascar help understand change mechanisms and hence, support decision-making to attain the Sustainable Development Goals.

Item Type:

Journal Article (Original Article)

Division/Institute:

10 Strategic Research Centers > Centre for Development and Environment (CDE)

Graduate School:

International Graduate School North-South (IGS North-South)

UniBE Contributor:

Llopis Sendino, Jorge Claudio

Subjects:

900 History > 910 Geography & travel

ISSN:

1747-4248

Publisher:

Taylor & Francis

Projects:

[1047] Managing Telecoupled Landscapes for Sustainable Provision of Ecosystem Services and Poeverty Alleviation
[803] Cluster: Land Resources

Language:

English

Submitter:

Stephan Schmidt

Date Deposited:

29 Jun 2020 17:09

Last Modified:

29 Jun 2020 17:09

Publisher DOI:

10.1080/1747423x.2020.1742810

Uncontrolled Keywords:

Bayesian networks, land-use decision modeling, drivers, land-use change, modeling

URI:

https://boris.unibe.ch/id/eprint/144111

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